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The main objective of this study is to investigate the relationship between the COVID-19 and the weather factors of the most populated and industrialised countries in Europe and propose the best mathematical model to forecast the daily number of COVID-19 cases. To find the relationship between the COVID-19 and the weather factors of absolute humidity and temperature in Spain, France, Italy, Germany, and the United Kingdom, we conducted a Poisson analysis. We also used the General Linear Neural Network (GRNN) model to forecast the trend and number of daily COVID-19 cases in these European countries. The results reveal a statistically significant negative relationship between the number of COVID-19 infections and weather factors of temperature & absolute humidity. Furthermore, the results show a stronger negative relationship between COVID-19 and absolute humidity than temperature. In our proposed GRNN method, we find better compatibility for the COVID-19 cases in Italy relative to the other European countries in this study.

This study explores the Iranian education to generate a curriculum that should be comprehensive of the rich inheritance of different variables like knowledge, skill and attitude. For that purpose, Service Quality (SERVQUAL) is a standard instrument to evaluation the level of quality provided. The present study is an attempt to measure the level of Service Quality provided by Zenithal in the field of technical education among management students. The results of the questionnaire survey are analyzed in relation to the five Service Quality (SERVQUAL) dimensions (tangibles; reliability; responsiveness; assurance; empathy) and revealed that various aspects of quality differ significantly based on some demographic variables.

This study examines the relationship between COVID-19 shocks and GDP loss of different countries worldwide based on the seven scenarios of the epidemiological DSGE/CGE model of [McKibbin, W., & Fernando, R. (2020). The Global Macroeconomic Impacts of COVID-19: Seven Scenarios. Asian Economic Papers, 20(2): 1-30, MIT Press]. We implemented a panel data approach for 24 cross-sectional units with three periods and a general regression neural network. The economic and financial shocks consist of labor supply, equity risk premium, consumption demand, and government expenditure. The findings show that the consumption demand and equity risk premium shocks on GDP are more influential than the other shocks. Moreover, the results reveal that the most significant GDP loss is associated with Japan, Germany, and the US, respectively, which are industrialized countries with the most prominent automobile manufacturers. The lowest GDP loss is linked to Saudi Arabia, one of the world's biggest oil producer countries.